Exemplo n.º 1
0
def _process_training(
    coords: np.ndarray,
    targets: np.ndarray,
    feature_source: H5Features,
    image_spec: ImageSpec,
    halfwidth: int,
) -> DataArrays:
    coords_x, coords_y = coords.T
    indices_x = world_to_image(coords_x, image_spec.x_coordinates)
    indices_y = world_to_image(coords_y, image_spec.y_coordinates)
    patch_reads, mask_reads = patch.patches(indices_x, indices_y, halfwidth,
                                            image_spec.width,
                                            image_spec.height)
    npatches = indices_x.shape[0]
    patchwidth = 2 * halfwidth + 1
    con_marray, cat_marray = None, None
    if feature_source.continuous:
        con_marray = _direct_read(feature_source.continuous, patch_reads,
                                  mask_reads, npatches, patchwidth)
    if feature_source.categorical:
        cat_marray = _direct_read(feature_source.categorical, patch_reads,
                                  mask_reads, npatches, patchwidth)
    indices = np.vstack((indices_x, indices_y)).T
    output = DataArrays(con_marray, cat_marray, targets, coords, indices)
    return output
Exemplo n.º 2
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def _process_query(indices: np.ndarray, feature_source: H5Features,
                   image_spec: ImageSpec, halfwidth: int) -> DataArrays:
    indices_x, indices_y = indices.T
    coords_x = image_to_world(indices_x, image_spec.x_coordinates)
    coords_y = image_to_world(indices_y, image_spec.y_coordinates)
    patch_reads, mask_reads = patch.patches(indices_x, indices_y, halfwidth,
                                            image_spec.width,
                                            image_spec.height)
    patch_data_slices = _slices_from_patches(patch_reads)
    npatches = indices_x.shape[0]
    patchwidth = 2 * halfwidth + 1
    con_marray, cat_marray = None, None
    if feature_source.continuous:
        con_data_cache = _get_rows(patch_data_slices,
                                   feature_source.continuous)
        con_marray = _cached_read(con_data_cache, feature_source.continuous,
                                  patch_reads, mask_reads, npatches,
                                  patchwidth)
    if feature_source.categorical:
        cat_data_cache = _get_rows(patch_data_slices,
                                   feature_source.categorical)
        cat_marray = _cached_read(cat_data_cache, feature_source.categorical,
                                  patch_reads, mask_reads, npatches,
                                  patchwidth)
    coords = np.vstack((coords_x, coords_y)).T
    output = DataArrays(con_marray, cat_marray, None, coords, indices)
    return output
Exemplo n.º 3
0
def test_patch_20():
    """Check patch code in y edge."""
    halfwidth = 1
    im_width = 5
    im_height = 5

    image = np.arange((im_height * im_width)).reshape((im_height, im_width))
    n = 2 * halfwidth + 1

    # 2,0 edge
    p_data = np.zeros((n, n), dtype=int) - 1
    x = np.array([2])
    y = np.array([0])
    patch_rws, mask_ws = patch.patches(x, y, halfwidth, im_width, im_height)
    for r in patch_rws:
        p_data[r.yp, r.xp] = image[r.y, r.x]
    true_answer = np.array([[-1, -1, -1], [1, 2, 3], [6, 7, 8]], dtype=int)
    assert np.all(true_answer == p_data)
Exemplo n.º 4
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def test_patch_44():
    """Check patch code in outer corner."""
    halfwidth = 1
    im_width = 5
    im_height = 5

    image = np.arange((im_height * im_width)).reshape((im_height, im_width))
    n = 2 * halfwidth + 1

    # 4,4 corner
    p_data = np.zeros((n, n), dtype=int) - 1
    x = np.array([4])
    y = np.array([4])
    patch_rws, mask_ws = patch.patches(x, y, halfwidth, im_width, im_height)
    for r in patch_rws:
        p_data[r.yp, r.xp] = image[r.y, r.x]
    true_answer = np.array([[18, 19, -1], [23, 24, -1], [-1, -1, -1]], dtype=int)
    assert np.all(true_answer == p_data)
Exemplo n.º 5
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def test_patch_44_mask():
    """Check that patches are correctly created from points in 00 corner."""
    halfwidth = 1
    im_width = 5
    im_height = 5
    n = 2 * halfwidth + 1

    #  0,0 corner
    p_mask = np.zeros((n, n), dtype=bool)
    x = np.array([4])
    y = np.array([4])
    patch_rws, mask_ws = patch.patches(x, y, halfwidth, im_width, im_height)
    for r in mask_ws:
        p_mask[r.yp, r.xp] = True

    true_answer = np.array(
        [[False, False, True], [False, False, True], [True, True, True]],
        dtype=bool)
    assert np.all(true_answer == p_mask)
Exemplo n.º 6
0
def test_patch_00():
    """Check that patches are correctly created from points in 00 corner."""
    halfwidth = 1
    im_width = 5
    im_height = 5

    image = np.arange((im_height * im_width)).reshape((im_height, im_width))
    n = 2 * halfwidth + 1

    #  0,0 corner
    p_data = np.zeros((n, n), dtype=int) - 1
    x = np.array([0])
    y = np.array([0])
    patch_rws, mask_ws = patch.patches(x, y, halfwidth, im_width, im_height)
    for r in patch_rws:
        p_data[r.yp, r.xp] = image[r.y, r.x]

    true_answer = np.array([[-1, -1, -1], [-1, 0, 1], [-1, 5, 6]], dtype=int)
    assert np.all(true_answer == p_data)